1,720,983 research outputs found
Boosting performance of incremental IDR/QR LDA - from sequential to chunk
No full textTraining data in the real world is often presented in random chunks. Yet existing sequential incremental IDR/QR LDA (sIncLDA) can only process data one instance after another. This thesis proposes a new chunk incremental IDR/QR LDA (cIncLDA) capable of processing multiple data instances at one time. sIncLDA updates the reduced within-class scatter matrix W by a QR decomposition of the centroid matrix for each newly-arrived data instance. It is assumed that the updated Q' ≈ Q for any data instance from an existing class and the updated W' ≈ W for any data instance from a new class. In practice, the assumption in sIncLDA leads to significant loss of the discriminative information from approximating Q and W when the number of classes is large. By utilizing a new method that accurately updates W, the proposed cIncLDA can better pr eserve the discriminative information contained in W. The limitation of sIncLDA is hence resolved. Experimental comparisons have been conducted on six facial datasets with diverse class numbers ranging from 40 to 1010. The result indicates that our algorithm achieves an competitive accuracy to batch QR/LDA and is consistently higher than sIncLDA. It is noted in the report that the computational complexity of our algorithm is more expensive than sIncLDA for single data processing (i.e., sequential manner); however, the efficiency of our algorithm surpasses sIncLDA as the chunk size increases for multiple instances processing (i.e., chunk manner)
CuWITH: A Curiosity Driven Robot for Office Environmental Security
No full textThe protection of assets is an important part of daily life. Currently this is done using a combination of passive security cameras and security officers actively patrolling the premises. However, security officers, being human, are subject to a number of limitations both physical and mental. A security robot would not suffer from these limitations, however currently there are a number of challenges to implementing such a robot. These challenges include navigation in a complex real-world environment, fast and accurate threat detection and threat tracking. Overcoming these challenges is the focus of my research.
To that end a small security robot, the CuWITH or Curious WITH,has been developed and is presented in this thesis. The CuWITH utilises a programmable navigation system, curiosity-based threat detection and curiosity-driven threat tracking curiosity to protect a real office environment.
In this thesis we will first discuss the CuWITH's system design in detail, with a particular focus on the components and the architectural strategies employed. We then move to a more detailed examination of the mathematical underpinnings of the CuWITHs curiosity based threat detection and curiosity driven threat tracking. The details of the CuWITH's navigation will also be explained.
We will then present a number of experiments which demonstrate the effectiveness of the CuWITH. We show that the programmable navigation of the CuWITH, although simple, allows for easy modification of the patrol path without risk to the stability of the system. We will then present the results of both offline and online testing of the CuWITH's curiosity based threat detection. The reaction time and accuracy of the CuWITHs curiosity driven threat tracking will also be illustrated.
As a final test the CuWITH is instructed to execute a patrol in a real office environment, with threatening and non-threatening persons present. The results of this test demonstrate all major systems of the CuWITH working together very well and successfully executing the patrol even when moved to a different environment
CuWITH: a curiosity driven robot for office environmental security
No full textThe protection of assets is an important part of daily life. Currently this is done using a combination of passive security cameras and security officers actively patrolling the premises. However, security officers, being human, are subject to a number of limitations both physical and mental. A security robot would not suffer from these limitations, however currently there are a number of challenges to implementing such a robot. These challenges include navigation in a complex real-world environment, fast and accurate threat detection and threat tracking. Overcoming these challenges is the focus of my research.
To that end a small security robot, the CuWITH or Curious WITH,has been developed and is presented in this thesis. The CuWITH utilises a programmable navigation system, curiosity-based threat detection and curiosity-driven threat tracking curiosity to protect a real office environment.
In this thesis we will first discuss the CuWITH's system design in detail, with a particular focus on the components and the architectural strategies employed. We then move to a more detailed examination of the mathematical underpinnings of the CuWITHs curiosity based threat detection and curiosity driven threat tracking. The details of the CuWITH's navigation will also be explained.
We will then present a number of experiments which demonstrate the effectiveness of the CuWITH. We show that the programmable navigation of the CuWITH, although simple, allows for easy modification of the patrol path without risk to the stability of the system. We will then present the results of both offline and online testing of the CuWITH's curiosity based threat detection. The reaction time and accuracy of the CuWITHs curiosity driven threat tracking will also be illustrated.
As a final test the CuWITH is instructed to execute a patrol in a real office environment, with threatening and non-threatening persons present. The results of this test demonstrate all major systems of the CuWITH working together very well and successfully executing the patrol even when moved to a different environment
Boosting Performance of Incremental IDR/QR LDA - From Sequential to Chunk
No full textTraining data in the real world is often presented in random chunks. Yet existing sequential incremental IDR/QR LDA (sIncLDA) can only process data one instance after another. This thesis proposes a new chunk incremental IDR/QR LDA (cIncLDA) capable of processing multiple data instances at one time. sIncLDA updates the reduced within-class scatter matrix W by a QR decomposition of the centroid matrix for each newly-arrived data instance. It is assumed that the updated Q' ≈ Q for any data instance from an existing class and the updated W' ≈ W for any data instance from a new class. In practice, the assumption in sIncLDA leads to significant loss of the discriminative information from approximating Q and W when the number of classes is large. By utilizing a new method that accurately updates W, the proposed cIncLDA can better pr eserve the discriminative information contained in W. The limitation of sIncLDA is hence resolved. Experimental comparisons have been conducted on six facial datasets with diverse class numbers ranging from 40 to 1010. The result indicates that our algorithm achieves an competitive accuracy to batch QR/LDA and is consistently higher than sIncLDA. It is noted in the report that the computational complexity of our algorithm is more expensive than sIncLDA for single data processing (i.e., sequential manner); however, the efficiency of our algorithm surpasses sIncLDA as the chunk size increases for multiple instances processing (i.e., chunk manner)
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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